This disclosure relates generally to the reconstruction of surfaces in three dimensional space from a two-dimensional image capture and, more particularly, to glyph encoded pattern instantiations of such images through use of glyph address codes (address carpet).
Reconstruction of accurate three-dimensional shapes (including moving and/or deforming shapes) from two-dimensional image captures is a longstanding and commercially important problem in computer vision. Structured light techniques attempt to solve the problem with controlled illumination, which operates by projecting certain known and controlled patterns onto the target object. By observing the distortion of the patterns on the surface of the object and applying projective geometry, it is possible to digitally reconstruct the three dimensional shape of the object. However, existing structured light techniques (typically using repeated patterns such as stripes or lattices) suffer from difficulties with slow calibration and ambiguous registration, especially for complex scenes with occlusions.
The ambiguity problem may be demonstrated by the following example of two spheres positioned such that one partially occludes the other from the view of the camera. There may be two problems in interpreting the image captured by the camera in this process. Firstly, there may be insufficient information to enable mapping of the stripes one-to-one back to the original pattern. Secondly, from the viewing angle of the camera, part of the object may be occluded, which results in a discontinuity in the projected pattern in the captured image. Because of this discontinuity, the relationship between the stripes on different spheres is unknown. These two problems, in general referred to as ambiguity problems, present a challenge in the triangulation step.
These problems can be alleviated by bar coding in time or in color space. In Hall-Holt and Rusinkiewicz, “Stripe Boundary Codes for Real-Time Structured-Light Range Scanning of Moving Objects”, ICCV 2001, Hall-Holt and Rusinkiewicz utilize a sequence of black and white stripe patterns in 4D space-time. Over a period of 4 frames, each stripe in each of the frames is turned on and off in a predetermined sequence, so that each stripe is uniquely identifiable in a large neighborhood if the on-off pattern is examined over a period of 4 frames. This technique works well except it is at the cost of sampling frequency.
The approach of bar-coding in color space is proposed by Zhang, Curless and Seitz, “Rapid Shape Acquisition Using Color Structured Light and Multi-pass Dynamic Programming”, 1st International Symposium on 3D Data Processing, Visualization, and Transmission, Padova, Italy, Jun. 19–21, 2002. This approach utilizes alternating color stripes as the illumination pattern, so that each group of adjacent color stripes is uniquely identifiable within a large neighborhood. This technique improves the sampling frequency, as pattern structure is readily identifiable. The order of the color stripes is carefully arranged so that each small group of color stripes can be uniquely identified. However, the color appearance on the object surface may interfere with color patterns and thus affects decodability and/or accuracy, which result in irregularities in the appearance of the object.
Unfortunately, none of these approaches provide accurate reconstruction of three-dimensional shapes from two-dimensional images of fast moving and/or deforming objects (for example, objects being rotated, translated, mutating, inserted or removed) having a wide variety of surface color appearances.